This paper presents a infeasible interior-point primal -dual affine scaling algorithm for linear programming. it is shown that the method is polynomial-time algorithm.
摘要本文对线性规划提出了一个不可行内点原始-对偶仿射尺度算法，并证明了算法是一个多项式时间算法。
The interior point method is a polynomial time algorithm for solving linear programming problem, and its number of iterations is independent on the size of system.
内点法是一种求解线性规划问题的多项式时间算法，其显著特征是其迭代次数与系统规模关系不大。
The simplex pivotal calculations based on the new criterion can reduce the iterations to the least. The new algorithm can save much CPU time, especially for the large-scale linear programming problem.
按该准则进行的枢轴运算，能使单纯形算法的迭代次数减到最少，尤其对大规划线性规划问题而言，该方法能节省相当可观的CPU计算时间。
The simplex pivotal calculations based on the new criterion can reduce the iterations to the least. The new algorithm can save much CPU time, especially for the large-scale linear programming problem.
按该准则进行的枢轴运算，能使单纯形算法的迭代次数减到最少，尤其对大规划线性规划问题而言，该方法能节省相当可观的CPU计算时间。
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